Chrome Extension
WeChat Mini Program
Use on ChatGLM

A nationwide mobile phone survey for tobacco use in Tanzania: Sample quality and representativeness compared to a household survey

PREVENTIVE MEDICINE REPORTS(2024)

Cited 0|Views16
No score
Abstract
We investigated the feasibility of an interactive voice response (IVR) survey in Tanzania and compared its prevalence estimates for tobacco use to the estimates of the 'Global Adult Tobacco Survey (GATS) 2018 '. IVR participants were enrolled by random digit dialing. Quota sampling was employed to achieve the required sample sizes of age-sex strata: sex (male/female) and age (18-29-, 30-44-, 45-59-, and >= 60-year-olds). GATS was a nationally representative survey and used a multistage stratified cluster sampling design. The IVR sample's weights were generated using the inverse proportional weighting (IPW) method with a logit model and the standard age-sex distribution of Tanzania. The IVR and GATS had 2362 and 4555 participants, respectively. Compared to GATS, the unweighted IVR sample had a higher proportion of males (58.7 % vs. 43.2 %), educated people (secondary/above education: 43.3 % vs. 21.1 %), and urban residents (56.5 % vs. 40 %). The weighted prevalence (95 % confidence interval (CI)) of current smoking was 4.99 % (4.11-6.04), 5.22 % (4.36-6.24), and 7.36 % (6.51-8.31) among IVR (IPW), IVR (age-sex standard), and GATS samples, respectively; the weighted prevalence (95 % CI) of smokeless tobacco use was similar: 3.54 % (2.73-4.57), 3.58 % (2.80-4.56), and 2.43 % (1.98-2.98), respectively. Most differences in point estimates for tobacco indicators were small (<2%). Overall, the odds of tobacco smoking indicators were lower in IVR than in GATS; however, the odds of smokeless tobacco use were reversed. Although we found under-/over-estimation of the prevalence of tobacco use in IVR than GATS, the estimates were close. Further research is required to increase the representativeness of IVR.
More
Translated text
Key words
Mobile phone survey,Survey findings,Interactive voice response,Tobacco use,Data collection
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined